




'''simple docstring'''







from dataclasses import dataclass
from typing import Optional, Tuple

import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput

@dataclass
class 	_snake_case(			UpperCAmelCase      ):
 __snake_case:							Optional[torch.FloatTensor]						=					None
 __snake_case:							torch.FloatTensor						=					None
 __snake_case:							Optional[Tuple[torch.FloatTensor]]						=					None
 __snake_case:							Optional[Tuple[torch.FloatTensor]]						=					None




class 	_snake_case(			UpperCAmelCase      ):






 def __init__(self       :  Any    ,		a       :  Any=1    ,		a       :  Optional[int]=0    ,		a       :  Union[str, Any]=2    ,		a       :  List[str]=5_12    ,		a       :  Optional[int]="cls"    ,		a       :  Union[str, Any]=False    ,		a       :  List[str]=True    ,		**a       :  str    ,		)       ->   Dict:






    """simple docstring"""


    super().__init__(pad_token_id=a    ,		bos_token_id=a    ,		eos_token_id=a    ,		**a    )
    A__       =     project_dim
    A__       =     pooler_fn
    A__       =     learn_encoder
    A__       =     use_attention_mask




class 	_snake_case(			UpperCAmelCase      ):
 __snake_case:							int						=					[R'''pooler''', R'''logit_scale''']
 __snake_case:							Dict						=					[R'''position_ids''', R'''predictions.decoder.bias''']
 __snake_case:							int						=					'''roberta'''
 __snake_case:							Union[str, Any]						=					RobertaSeriesConfig






 def __init__(self       :  Dict    ,		a       :  Dict    )       ->   int:






    """simple docstring"""


    super().__init__(a    )
    A__       =     XLMRobertaModel(a    )
    A__       =     nn.Linear(config.hidden_size    ,		config.project_dim    )
    A__       =     getattr(a    ,		'has_pre_transformation'    ,		a    )
    if self.has_pre_transformation:
       A__       =     nn.Linear(config.hidden_size    ,		config.project_dim    )
       A__       =     nn.LayerNorm(config.hidden_size    ,		eps=config.layer_norm_eps    )
    self.post_init()






 def 						_UpperCamelCase (self       :  Any    ,		a       :  Optional[torch.Tensor] = None    ,		a       :  Optional[torch.Tensor] = None    ,		a       :  Optional[torch.Tensor] = None    ,		a       :  Optional[torch.Tensor] = None    ,		a       :  Optional[torch.Tensor] = None    ,		a       :  Optional[torch.Tensor] = None    ,		a       :  Optional[torch.Tensor] = None    ,		a       :  Optional[torch.Tensor] = None    ,		a       :  Optional[bool] = None    ,		a       :  Optional[bool] = None    ,		a       :  Optional[bool] = None    ,		)       ->   int:






    """simple docstring"""


    A__       =     return_dict if return_dict is not None else self.config.use_return_dict

    A__       =     self.base_model(
        input_ids=a    ,		attention_mask=a    ,		token_type_ids=a    ,		position_ids=a    ,		head_mask=a    ,		inputs_embeds=a    ,		encoder_hidden_states=a    ,		encoder_attention_mask=a    ,		output_attentions=a    ,		output_hidden_states=True if self.has_pre_transformation else output_hidden_states    ,		return_dict=a    ,		)

    if self.has_pre_transformation:
       A__       =     outputs['hidden_states'][-2]
       A__       =     self.pre_LN(a    )
       A__       =     self.transformation_pre(a    )

       return TransformationModelOutput(
           projection_state=a    ,		last_hidden_state=outputs.last_hidden_state    ,		hidden_states=outputs.hidden_states    ,		attentions=outputs.attentions    ,		)
    else:
       A__       =     self.transformation(outputs.last_hidden_state    )
       return TransformationModelOutput(
           projection_state=a    ,		last_hidden_state=outputs.last_hidden_state    ,		hidden_states=outputs.hidden_states    ,		attentions=outputs.attentions    ,		)








'''simple docstring'''







# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

lowerCAmelCase_     						=				'''2.13.1'''

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('''3.7'''):
    raise ImportWarning(
        '''To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'''
    )

if version.parse(pyarrow.__version__).major < 8:
    raise ImportWarning(
        '''To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'''
        '''If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'''
    )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

lowerCAmelCase_     						=				concatenate_datasets
lowerCAmelCase_     						=				DownloadConfig
lowerCAmelCase_     						=				DownloadManager
lowerCAmelCase_     						=				DownloadMode
lowerCAmelCase_     						=				DownloadConfig
lowerCAmelCase_     						=				DownloadMode
lowerCAmelCase_     						=				DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager


